def unify(constraints, broadcasting=None):
"""
Unify a set of constraints and return a concrete solution
>>> import blaze
>>> d1 = blaze.dshape('10, int32')
>>> d2 = blaze.dshape('T, float32')
>>> [result], constraints = unify([(d1, d2)], [True])
>>> result
dshape("10, float32")
>>> constraints
[]
"""
S = IdentityDict()
constraints = [(simplify(ds1, S), simplify(ds2, S))
for ds1, ds2 in constraints]
# Compute a solution to a set of constraints
constraints, b_env = normalize(constraints, broadcasting)
logger.debug("Normalized constraints: %s", constraints)
solution, remaining = unify_constraints(constraints, S)
logger.debug("Initial solution: %s", solution)
seed_typesets(remaining, solution)
merge_typevar_sets(remaining, solution)
# Compute a type substitution with concrete types from the solution
# TODO: incorporate broadcasting environment during reification
substitution = reify(solution)
logger.debug("Substitution: %s", substitution)
# Reify and promote the datashapes
result = [substitute(substitution, ds2) for ds1, ds2 in constraints]
return result, remaining
def test_normalize_ellipses_2_ellipses2(self):
ds1 = dshape('A, ..., B, int32')
ds2 = dshape('M, N, ..., S, T, float32')
res1, res2 = normalize(ds1, ds2)
self.assertEqual(str(res1), 'A, N, ..., S, B, int32')
self.assertEqual(str(res2), 'M, N, ..., S, T, float32')
def test_normalize_ellipses_2_ellipses(self):
ds1 = dshape('..., A, int32')
ds2 = dshape('X, ..., Y, Z, float32')
res1, res2 = normalize(ds1, ds2)
self.assertEqual(str(res1), 'X, ..., Y, A, int32')
self.assertEqual(str(res2), 'X, ..., Y, Z, float32')
def test_normalize_ellipses5(self):
ds1 = dshape('..., A, B, int32')
ds2 = dshape('..., X, Y, float32')
res1, res2 = normalize(ds1, ds2)
self.assertEqual(str(res1), '..., A, B, int32')
self.assertEqual(str(res2), '..., X, Y, float32')
def test_normalize_ellipses1(self):
ds1 = dshape('..., T')
ds2 = dshape('X, Y, T')
res1, res2 = normalize(ds1, ds2)
self.assertEqual(str(res1), 'X, Y, T')
self.assertEqual(str(res2), 'X, Y, T')
def test_normalize_ellipsis_broadcasting(self):
ds1 = dshape('T, int32 -> T, T, int32')
ds2 = dshape('A..., int32 -> A..., float32')
[(x, y)], _ = normalize([(ds1, ds2)])
self.assertEqual(str(y), 'T, int32 -> T, T, float32')
